Neuronavigation-assisted bedside placement of bolt external ventricular drains in the intensive care setting: a technical note

Background: The insertion of bolt external ventricular drains (EVD) on the intensive care unit (ICU) has enabled rapid cranial cerebrospinal fluid (CSF) diversion. However, bolt EVDs tend to be perceived as a more challenging technique, particularly when dealing with small ventricles or when there is midline shift distorting the ventricular morphology. Furthermore, if neuronavigation guidance is felt to be necessary, this usually assumes a transfer to an operating theatre. In this technical note, we describe the use of electromagnetic neuronavigation for bolt EVD insertion on the ICU and assess the protocol’s feasibility and accuracy. / Methods: Case series of neuronavigation-assisted bolt EVD insertion in ICU setting, using Medtronic Flat Emitter for StealthStation EM. / Results: Neuronavigation-guided bolt EVDs were placed at the bedside in n = 5 patients on ICU. Their widest frontal ventricular horn diameter in the coronal plane ranged from 11 to 20 mm. No procedural complications were encountered. Post-procedural CT confirmed the optimal placement of the EVDs. / Conclusions: Electromagnetic neuronavigation is feasible at the ICU bedside and can assist the insertion of bolt EVDs in this setting. The preference for a bolt EVD to be inserted in ICU—as is standard practice at this unit—should not prohibit patients from benefitting from image guidance if required

MMSAT: Automated quantification of metabolites in selected reaction monitoring experiments

Selected reaction monitoring (SRM) is a mass spectrometry-based approach commonly used to increase analytical sensitivity and selectively for specific compounds in complex metabolomic samples. While the goal of well-designed SRM methods is to monitor for unique precursor-product ion pairs, in practice this is not always possible due to the diversity of the metabome and the resolution limits of mass spectrometers that are capable of SRM. Isobaric or near-isobaric precursor ions with different chromatographic properties but identical product ions often arise in complex samples. Without analytical standards, such metabolites will go undetected by conventional data analysis methods. Furthermore, a single SRM method may include simultaneous monitoring of tens to hundreds of different metabolites across multiple samples making quantification of all detected ions a challenging task. To facilitate the analysis of SRM data from complex metabolomic samples, we have developed the Metabolite Mass Spectrometry Analysis Tool (MMSAT). MMSAT is a web-based tool that objectively quantifies every metabolite peak detected in a set of samples and aligns peaks across multiple samples to enable quantitative comparison of each metabolite between samples. The analysis incorporates quantification of multiple peaks/ions that have different chromatographic retention times but are detected within a single SRM transition. We compare the performance of MMSAT against existing tools using a human glioblastoma tissue extract and illustrate its ability to automatically quantify multiple precursors within each of three different transitions. The Web-interface and source code is avaliable at http://www.cancerresearch.unsw.edu.au/crcweb.nsf/page/MMSAT. © 2011 American Chemical Society.Link_to_subscribed_fulltex

<i>MMSAT</i>: Automated Quantification of Metabolites in Selected Reaction Monitoring Experiments

Selected reaction monitoring (SRM) is a mass spectrometry-based approach commonly used to increase analytical sensitivity and selectively for specific compounds in complex metabolomic samples. While the goal of well-designed SRM methods is to monitor for unique precursor–product ion pairs, in practice this is not always possible due to the diversity of the metabome and the resolution limits of mass spectrometers that are capable of SRM. Isobaric or near-isobaric precursor ions with different chromatographic properties but identical product ions often arise in complex samples. Without analytical standards, such metabolites will go undetected by conventional data analysis methods. Furthermore, a single SRM method may include simultaneous monitoring of tens to hundreds of different metabolites across multiple samples making quantification of all detected ions a challenging task. To facilitate the analysis of SRM data from complex metabolomic samples, we have developed the Metabolite Mass Spectrometry Analysis Tool (<i>MMSAT</i>). <i>MMSAT</i> is a web-based tool that objectively quantifies every metabolite peak detected in a set of samples and aligns peaks across multiple samples to enable quantitative comparison of each metabolite between samples. The analysis incorporates quantification of multiple peaks/ions that have different chromatographic retention times but are detected within a single SRM transition. We compare the performance of <i>MMSAT</i> against existing tools using a human glioblastoma tissue extract and illustrate its ability to automatically quantify multiple precursors within each of three different transitions. The Web-interface and source code is avaliable at http://www.cancerresearch.unsw.edu.au/crcweb.nsf/page/MMSAT